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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Anomalous magnetic noise in an imperfectly flat landscape in the topological magnet Dy 2 Ti 2 O 7

Noise generated by motion of charge and spin provides a unique window into materials at the atomic scale. From temperature of resistors to electrons breaking into fractional quasiparticles, “listening” to the noise spectrum is a powerful way to decode underlying dynamics. Here, we use ultrasensitive superconducting quantum interference device (SQUIDs) to probe the puzzling noise in a frustrated magnet, the spin-ice compound Dy 2 Ti 2 O 7 (DTO), revealing cooperative and memory effects. DTO is a topological magnet in three dimensions—characterized by emergent magnetostatics and telltale fractionalized magnetic monopole quasiparticles—whose real-time dynamical properties have been an enigma from the very beginning. We show that DTO exhibits highly anomalous noise spectra, differing significantly from the expected Brownian noise of monopole random walks, in three qualitatively different regimes: equilibrium spin ice, a “frozen” regime extending to ultralow temperatures, and a high-temperature “anomalous” paramagnet. We present several distinct mechanisms that give rise to varied colored noise spectra. In addition, we identify the structure of the local spin-flip dynamics as a crucial ingredient for any modeling. Thus, the dynamics of spin ice reflects the interplay of local dynamics with emergent topological degrees of freedom and a frustration-generated imperfectly flat energy landscape, and as such, it points to intriguing cooperative and memory effects for a broad class of magnetic materials.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Cooling and Timing Tests of the ATLAS Fast TracKer VME Boards

The Fast TracKer (FTK) is an ATLAS trigger upgrade built for full-event, low-latency, high-rate tracking. The FTK core, made of 9U VME boards, performs the most demanding computational task. The associative memory board (AMB) serial link processor and the auxiliary card (AUX), plugged on the front and back sides of the same VME slot, constitute the processing unit (PU), which finds tracks using hits from eight layers of the inner detector. The PU works in pipeline with the second stage board (SSB), which finds 12-layer tracks by adding extra hits to the identified tracks. In the designed configuration, 16 PUs and four SSBs are installed in a VME crate. The high power consumption of the AMB, AUX, and SSB (respectively, of about 250, 70, and 160 W per board) required the development of a custom cooling system. Even though the expected power consumption for each VME crate of the FTK system is high compared with a common VME setup, the 8 FTK core crates will use ≈60 kW, which is just a fraction of the power and the space needed for a CPU farm performing the same task. We report on the integration of 32 PUs and eight SSBs inside the FTK system, on the infrastructures needed to run and cool them, and on the tests performed to verify the system processing rate and the temperature stability at a safe value.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Battery Monitoring System

The component that is powered by the battery pack being monitored is a valuable asset and must be in working condition at all times. Battery chemistry and characteristics have a major role in how to evaluate the state of the battery. The battery monitoring system has many parts that lead to an accurate battery reading. The components consist of a coulomb counting device, end of life voltage detection, a consideration of use for a real-time clock (RTC), temperature sensor, and non-volatile random-access memory (NVRAM). The combination of these elements allows the monitoring system to be highly reliant. Moving forward a better implementation of the ideas in this paper and further testing should ensure a high-quality battery monitoring system.

25 ENERGY STORAGE↗
DOE OSTI2024

Evaluating Operators in Deep Neural Networks for Improving Performance Portability of SYCL

SYCL is a portable programming model for heterogeneous computing, so it is important to obtain reasonable performance portability of SYCL. Towards the goal of better understanding and improving performance portability of SYCL for machine learning workloads, we have been developing benchmarks for basic operators in deep neural networks (DNNs). These operators could be offloaded to heterogeneous computing devices such as graphics processing units (GPUs) to speed up computation. In this work, we introduce the benchmarks, evaluate the performance of the operators on GPU-based systems, and describe the causes of the performance gap between the SYCL and Compute Unified Device Architecture (CUDA) kernels. We find that the causes are related to the utilization of the texture cache for read-only data, optimization of the memory accesses with strength reduction, shared local memory accesses, and register usage per thread. We hope that the efforts of developing benchmarks for studying performance portability will stimulate discussion and interactions within the community.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Probing Dynamic Phase Changes in Electrochemical Systems with Cryogenic and in Situ Analytical Electron Microscopy (Final Technical Report)

In this project, we focus on the advancement of our newly developed, unique in situ and cryogenic analytical electron microscopy (AEM) techniques and the development of additional high-end capabilities to quantitatively elucidate the mechanisms of resistive state changes in solid-state electrochemical materials for non-volatile, neuromorphic memory. The objectives of the proposed research are (1) to characterize and elucidate the mechanisms by which electronic state changes occur in various solid-state devices to build guiding principles for electrochemically activated smart materials; (2) to advance our understanding of such mechanisms by coupling cryogenic and in situ techniques to control kinetics of the observed mechanisms while mitigating probe-induced damage; and (3) to utilize additional advanced techniques including electron-beam induced current and quantum mechanical simulations in order to identify the underlying fundamental science of such processes, including roles of defect formation and its effect on phase nucleation, as well as dynamics of these processes in the electrochemical systems at the nanometer scale.

25 ENERGY STORAGE↗
NASA NTRS1978

Test-vehicle cycle programmer

Instrument reduces manpower needed for testing electric powered vehicles. Device has dual scale that allows operator to compare actual speed with preprogrammed test speed. Features include large meter, buzzer, packaging to allow ready interchange of memories with different profiles, small size, minimal current drain, and reverse supply voltage protection.

Lesco, D. J.↗
DOE OSTI2025

Erbium quantum memory platform with long optical coherence via back-end-of-line deposition on foundry-fabricated photonics

Realizing scalable quantum interconnects necessitates the integration of solid-state quantum memories with foundry photonics processes. While prior photonic integration efforts have relied upon specialized, laboratory-scale fabrication techniques, this work demonstrates the monolithic integration of a quantum memory platform with low-loss foundry photonic circuits via back-end-of-line deposition. We deposited thin films of titanium dioxide (Ti⁢O 2 ) doped with erbium (Er) onto silicon nitride nanophotonic waveguides and studied Er optical coherence at subkelvin temperatures with photon echo techniques. Furthermore, we suppressed optical dephasing through ex-situ oxygen annealing and optimized measurement conditions, which yielded an optical coherence time of 64 μ⁢s (a 5-kHz homogeneous linewidth) and slow spectral diffusion of 27 kHz over 4 ms, results that are comparable to state-of-the-art Er nanophotonic devices. Combined with second-long electron spin lifetimes and demonstrated electrical control of Er emission, our findings establish Er:Ti⁢O 2 on foundry photonics as a manufacturable platform for ensemble and single-ion quantum memories.

Electro-optic effects↗
DOE OSTI2024

Energy efficient photonic memory based on electrically programmable embedded III-V/Si memristors: switches and filters

Abstract Over the past few years, extensive work on optical neural networks has been investigated in hopes of achieving orders of magnitude improvement in energy efficiency and compute density via all-optical matrix-vector multiplication. However, these solutions are limited by a lack of high-speed power power-efficient phase tuners, on-chip non-volatile memory, and a proper material platform that can heterogeneously integrate all the necessary components needed onto a single chip. We address these issues by demonstrating embedded multi-layer HfO 2 /Al 2 O 3 memristors with III-V/Si photonics which facilitate non-volatile optical functionality for a variety of devices such as Mach-Zehnder Interferometers, and (de-)interleaver filters. The Mach-Zehnder optical memristor exhibits non-volatile optical phase shifts > π with ~33 dB signal extinction while consuming 0 electrical power consumption. We demonstrate 6 non-volatile states each capable of 4 Gbps modulation. (De-) interleaver filters were demonstrated to exhibit memristive non-volatile passband transformation with full set/reset states. Time duration tests were performed on all devices and indicated non-volatility up to 24 hours and beyond. We demonstrate non-volatile III-V/Si optical memristors with large electric-field driven phase shifts and reconfigurable filters with true 0 static power consumption. As a result, co-integrated photonic memristors offer a pathway for in-memory optical computing and large-scale non-volatile photonic circuits.

Cheung, Stanley (ORCID:0000000248860013)↗
DOE OSTI2024

Effect of fabrication processes on BaTiO 3 capacitor properties

There is an increasing desire to utilize complex functional electronic materials such as ferroelectrics in next-generation microelectronics. As new materials are considered or introduced in this capacity, an understanding of how we can process these materials into those devices must be developed. Here, the effect of different fabrication processes on the ferroelectric and related properties of prototypical metal oxide (SrRuO 3 )/ferroelectric (BaTiO 3 )/metal oxide (SrRuO 3 ) heterostructures is explored. Two different types of etching processes are studied, namely, wet etching of the top SrRuO 3 using a NaIO 4 solution and dry etching using an Ar + -ion beam (i.e., ion milling). Polarization-electric-field hysteresis loops for capacitors produced using both methods are compared. For the ion-milling process, it is found that the Ar + beam can introduce defects into the SrRuO 3 /BaTiO 3 /SrRuO 3 devices and that the milling depth strongly influences the defect level and can induce a voltage imprint on the function. Realizing that such processing approaches may be necessary, work is performed to ameliorate the imprint of the hysteresis loops via ex situ “healing” of the process-induced defects by annealing the ferroelectric material in a barium-and-oxygen-rich environment via a chemical-vapor-deposition-style process. This work provides a pathway for the nanoscale fabrication of these candidate materials for next-generation memory and logic applications.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Electrode and Microstructure Dependence of Oxygen Diffusion in Ferroelectric Hafnium Zirconium Oxide Thin Films

Hafnia-based ferroelectrics hold promise to reduce energy demand for computing by enabling compute-in-memory and as non-volatile memories. The ferroelectric phase in this material system is, in part, stabilized by oxygen vacancies. While oxygen vacancies may be a necessity for phase stability, they limit device endurance through diffusion and accumulation into conducting channels. Herein, it is shown that oxygen diffusion is spatially variable within individual grains of ferroelectric hafnium zirconium oxide (HZO). Using 18 O tracers and finite difference modeling, it is shown that grain boundaries and regions near electrode interfaces allow for relatively rapid oxygen diffusion, with values as much as 10 4 larger than the grain cores. Further, the selection of electrode material affects the diffusion coefficients across all microstructural regions. HZO films in contact with TiN electrodes result in more oxygen-deficient HZO films and higher oxygen diffusion coefficients. Tungsten electrodes result in fewer vacancies and lower diffusion coefficients. Diffusion activation energy differences between the HZO with the two electrodes is reconciled by differing populations of charged and uncharged oxygen vacancies. This insight into the local vacancy populations and diffusion pathways provides a platform for designing hafnia-based films, deposition processes, and integration strategies to reduce vacancy gradients and improve performance.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Aluminum Boron Nitride Ferroelectric Field-Effect Transistors With ZnO Semiconductor Channel

The discovery of ferroelectricity in hafnium zirconium oxide (HfxZr 1−x O2) and related fluorite materials has spurred interest in ferroelectric devices suitable for integration with silicon integrated circuits (ICs), especially those that can be embedded in the back-end-of-line (BEOL) process. More recently, ferroelectricity has been found in wurtzite aluminum nitride-based materials, such as scandium and boron-doped aluminum nitride (Al 1−x ScxN and Al 1−x BxN). Although these materials currently have undesirably large coercive electric fields, and small breakdown electric field-to-coercive electric field ratio, their low processing temperatures and large remanent polarization offer intriguing possibilities for device applications. Furthermore, we report ferroelectric field-effect transistors (FeFETs) with a 15 nm thick Al0.88B0.12N layer and an 11 nm ZnO semiconductor channel, achieving a memory window >1 V and switching voltages ( V switch ) <±10 V.

42 ENGINEERING↗
NASA NTRS1990

Programmable synaptic devices for electronic neural nets

The architecture, design, and operational characteristics of custom VLSI and thin film synaptic devices are described. The devices include CMOS-based synaptic chips containing 1024 reprogrammable synapses with a 6-bit dynamic range, and nonvolatile, write-once, binary synaptic arrays based on memory switching in hydrogenated amorphous silicon films. Their suitability for embodiment of fully parallel and analog neural hardware is discussed. Specifically, a neural network solution to an assignment problem of combinatorial global optimization, implemented in fully parallel hardware using the synaptic chips, is described. The network's ability to provide optimal and near optimal solutions over a time scale of few neuron time constants has been demonstrated and suggests a speedup improvement of several orders of magnitude over conventional search methods.

Moopenn, A.↗
NASA NTRS1996

Performance of a Smart Vibration Isolator for Precision Spacecraft Instruments

Under the ARPA SMS Partnership Program for Synthesis and Processing of Smart Materials, Lockheed Missiles and Space company, Inc. has developed a demonstration prototype vibration cancelling mount using electrostrictive ceramic and shape-memory alloy actuators. Shape-memory actuators provide an adaptive-passive, self-damping support for isolation, while the electrostrictive actuators are employed to provide force and position control. The demonstration device was designed to address generic requirements for vibration stabilization of precision spacecraft instruments. It is reconfigurable to operate in any of four modes; passive isolation, active-passive isolation using force cancellation, active precision positioning, and active disturbance rejection. The presentation summarizes design of the device design and results of experimental evaluations of the device in isolation (active and passive) and positioning modes. Rejection of payload-borne disturbances is also discussed with reference to predictions from experimentally calibrated simulations. Finally, avenues for further development and refinement of the device are discussed.

Regelbrugge, Marc E.↗
NASA NTRS1996

Real Sky Performance of the Prototype sted Advanced Stellar Compass

The Danish microsatellite, sted, is equipped with an autonomous, advanced stellar compass (ASC). The ASC consists of two separate units, a Charge Coupled Device (CCD) camera head (based on a commercial Sony interline CCD detector) and a data processing unit with a powerful microcomputer (Intel 80486 type processor). The microcomputer memory contains a star catalogue which enables the microcomputer to recognize the constellations of stars in the field of vies and thus derive the attitude of the ASC camera head. The mission, and the design, operation and performance of the ASC are described. Results of the ASC prototype tests at the Jet Propulsion Laboratory (JPL) Table Mountain Observatory (TMO) facility are given.

orstedautonomous advanced stellar compass ASC adva↗
DOE OSTI2022

Smart material based multilayered microbeam structures for spatial self-deployment and reconfiguration: A residual stress approach

Alleviation of the potentially damaging effects induced by residual stresses was comprehensively investigated in previous research. Here, this paper, however, presents a spatially self-deployable and reconfigurable multilayered microbeam which takes advantage of residual stresses and shape memory effects. Reconfigurable mechanism of a typical four-layered microbeam composed of Pt\Ni 50 Ti 50 \Ni 50 Ti 50 \Pt is introduced, followed by analytical modeling of the maximum distance of the self-deployed gap as functions of variable structural and material parameters, including compressive residual stress in Pt layers and tensile residual stress in Ni 50 Ti 50 layers. Analytical solutions given by the static model agree well with the results obtained via finite element models (FEMs). Fabrication, characterization, and in-situ experiments were carried out to validate the feasibility of deployment of the as-released four-layered microbeam. The maximum distance of the gap was measured to be 41.39 μm at 20 °C, which could be increased to 51.73 μm thanks to controllable reconfiguration driven by shape memory effects. Theoretical analysis of such self-deployment and reconfiguration suggested a tensile residual stress increase by 52 MPa in Ni 50 Ti 50 layers. The multilayered microbeam structure with capabilities of self-deployment and reconfiguration offers great potential for various emerging applications, such as micro robotics, medical drug delivery devices, and intelligent chip scale spacecraft.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Software-Hardware Co-design of Heterogeneous SmartNIC System for Recommendation Models Inference and Training

Deep Learning Recommendation Models (DLRMs) are critical applications in various domains and have evolved as one of the single largest machine learning applications. Trillions of DLRM parameters exceed the on-chip memory capacity of GPUs. Large-scale multi-node systems are required for distributed DLRM inference and training, which suffer from the all-to-all communication bottleneck, mainly limiting the scalability of ever-growing DLRMs. In recent years, SmartNICs have evolved with coupled computation and communication capabilities providing opportunities for a powerful heterogeneous device in the system. However, there isn't such a distributed system that fully leverages the abundant smartNIC resources that resolve the scalability issue of DLRMs. In this work, we proposed a software-hardware co-design of a heterogeneous smartNIC system that resolves the communication bottleneck of distributed DLRMs, mitigates the memory bandwidth pressure, and improves computation efficiency. We provide a set of smartNIC designs of cache systems (including local cache and remote cache) and smartNIC computation kernels which reduce data movement, relieve memory lookup intensity, and improve the GPU's computation efficiency. In addition, we propose a graph algorithm that improves the data locality of queries within batches which optimizes the overall system performance with higher data reuse. Our evaluation shows that our system achieves 2.1x latency speedup for inference and 1.6x throughput speedup for training.

Guo, Anqi↗
DOE OSTI2026

Using Explainable Artificial Intelligence to Predict Perovskite Solar Cell Electrical Metastability from Operando Photoluminescence Images in Accelerated Stress Testing

Metal halide perovskite (MHP) solar cells exhibit a metastable response to bias governed by coupled ionic–electronic processes, complicating the conventional reciprocity relation between luminescence intensity and device open-circuit voltage (V oc ). This limits the use of luminescence as a diagnostic for device screening or accelerated stress testing, motivating new approaches that can interpret photoluminescence (PL) signals under nonequilibrium conditions. From the artificial intelligence perspective, we develop an explainable deep learning framework that integrates convolutional neural networks (CNN), long short-term memory (LSTM) layers, and an attention mechanism to learn spatiotemporal features from operando photoluminescence PL image sequences. The model achieves a mean absolute error of ±0.027 V in predicting open-circuit voltage transients and reduces extreme-tail errors by up to 78% compared to physics-based reciprocity calculations. Gradient-weighted Class Activation Mapping (Grad-CAM) provides interpretability by highlighting physically meaningful regions such as electrode edges and emergent defect features. From the engineering application perspective, this framework enables accurate, contactless prediction of device V oc and identification of degradation-relevant features during accelerated aging of perovskite solar cells. This approach demonstrates how explainable AI can enhance operando diagnostics and reliability analysis in photovoltaic devices under nonequilibrium conditions.

14 SOLAR ENERGY↗
DOE OSTI2025

Polarization rotation in a ferroelectric BaTiO 3 film through low-energy He-implantation

Domain engineering in ferroelectric thin films is crucial for next-generation microelectronic and photonic technologies. Here, a method is demonstrated to precisely control domain configurations in BaTiO 3 thin films through low-energy He ion implantation. The approach transforms a mixed ferroelectric domain state with significant in-plane polarization into a uniform out-of-plane tetragonal phase by selectively modifying the strain state in the film’s top region. This structural transition significantly improves domain homogeneity and reduces polarization imprint, leading to symmetric ferroelectric switching characteristics. The demonstrated ability to manipulate ferroelectric domains post-growth enables tailored functional properties without compromising the coherently strained bottom interface. The method’s compatibility with semiconductor processing and ability to selectively modify specific regions make it particularly promising for practical implementation in integrated devices. This work establishes a versatile approach for strain-mediated domain engineering that could be extended to a wide range of ferroelectric systems, providing new opportunities for memory, sensing, and photonic applications where precise control of polarization states is essential.

36 MATERIALS SCIENCE↗